Recommendations to improve downloads of large earth observation data

被引:0
|
作者
Ramachandran R. [1 ]
Lynnes C. [2 ]
Baynes K. [2 ]
Murphy K. [3 ]
Baker J. [4 ]
Kinney J. [4 ]
Gold A. [4 ]
Sundwall J. [4 ]
Korver M. [4 ]
Lieber A. [5 ]
Vambenepe W. [5 ]
Hancher M. [5 ]
Moore R. [5 ]
Erickson T. [5 ]
Henretig J. [6 ]
Zwiefel B. [6 ]
Patrick-Ahlstrom H. [6 ]
Smith M.J. [6 ]
机构
[1] Ramachandran, Rahul
[2] Lynnes, Christopher
[3] Baynes, Kathleen
[4] Murphy, Kevin
[5] Baker, Jamie
[6] Kinney, Jamie
[7] Gold, Ariel
[8] Sundwall, Jed
[9] Korver, Mark
[10] Lieber, Allison
[11] Vambenepe, William
[12] Hancher, Matthew
[13] Moore, Rebecca
[14] Erickson, Tyler
[15] Henretig, Josh
[16] Zwiefel, Brant
[17] Patrick-Ahlstrom, Heather
[18] Smith, Matthew J.
关键词
Best practices; Cloud; Earth observation data; Large data transfers;
D O I
10.5334/dsj-2018-002
中图分类号
学科分类号
摘要
With the volume of Earth observation data expanding rapidly, cloud computing is quickly changing the way these data are processed, analyzed, and visualized. Collocating freely available Earth observation data on a cloud computing infrastructure may create opportunities unforeseen by the original data provider for innovation and value-added data re-use, but existing systems at data centers are not designed for supporting requests for large data transfers. A lack of common methodology necessitates that each data center handle such requests from different cloud vendors differently. Guidelines are needed to support enabling all cloud vendors to utilize a common methodology for bulk-downloading data from data centers, thus preventing the providers from building custom capabilities to meet the needs of individual vendors. This paper presents recommendations distilled from use cases provided by three cloud vendors (Amazon, Google, and Microsoft) and are based on the vendors’ interactions with data systems at different Federal agencies and organizations. These specific recommendations range from obvious steps for improving data usability (such as ensuring the use of standard data formats and commonly supported projections) to non-obvious undertakings important for enabling bulk data downloads at scale. These recommendations can be used to evaluate and improve existing data systems for high-volume data transfers, and their adoption can lead to cloud vendors utilizing a common methodology. © 2018 The Author(s).
引用
收藏
相关论文
共 50 条
  • [1] Detection and attribution of large spatiotemporal extreme events in Earth observation data
    Zscheischler, Jakob
    Mahecha, Miguel D.
    Harmeling, Stefan
    Reichstein, Markus
    ECOLOGICAL INFORMATICS, 2013, 15 : 66 - 73
  • [2] EARTH OBSERVATION DATA POLICY
    GIBSON, R
    SPACE POLICY, 1993, 9 (04) : 272 - 272
  • [3] Archives for Earth observation data
    Harris, R
    Olby, N
    SPACE POLICY, 2000, 16 (03) : 223 - 227
  • [4] Fusing GEDI with earth observation data for large area aboveground biomass mapping
    Shendryk, Yuri
    INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2022, 115
  • [5] Earth Observation for Urban Planning and Management - State of the art and recommendations for application of Earth Observation in Urban Planning
    Nichol, Janet
    King, Bruce
    Quattrochi, Dale
    Dowman, Ian
    Ehlers, Manfred
    Ding, Xiaoli
    PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING, 2007, 73 (09): : 973 - 979
  • [6] The interaction effects of information cascades, system recommendations and recommendations on software downloads
    Park, JiHye
    Park, JaeHong
    Yoon, Ho-Jung
    ONLINE INFORMATION REVIEW, 2019, 43 (05) : 728 - 742
  • [7] The digital Earth Observation Librarian: a data mining approach for large satellite images archives
    Datcu, Mihai
    Grivei, Alexandru-Cosmin
    Espinoza-Molina, Daniela
    Dumitru, Corneliu Octavian
    Reck, Christoph
    Manilici, Vlad
    Schwarz, Gottfried
    BIG EARTH DATA, 2020, 4 (03) : 265 - 294
  • [8] SAMPLING BASED IMAGE SPLITTING IN LARGE SCALE DISTRIBUTED COMPUTING OF EARTH OBSERVATION DATA
    Xing, Jin
    Sieber, Renee
    2014 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2014, : 1409 - 1412
  • [9] GridFlow for earth observation data processing
    Aloisio, G
    Cafaro, M
    Carteni, G
    Epicoco, I
    Quarta, G
    Raolil, S
    GCA '05: PROCEEDINGS OF THE 2005 INTERNATIONAL CONFERENCE ON GRID COMPUTING AND APPLICATIONS, 2005, : 168 - 174
  • [10] EARTH OBSERVATION DATA PRICING POLICY
    HARRIS, R
    KRAWEC, R
    SPACE POLICY, 1993, 9 (04) : 299 - 318